Overall evaluation of Skylab imagery for mapping of Latin America

The author has identified the following significant results. Skylab imagery is both desired and needed by the Latin American catographic agencies. The imagery is cost beneficial for the production of new mapping and maintenance of existing maps at national topographic series scales. If this information was available on a near time routine coverage basis, it would provide an excellent additional data base to the Latin American cartographic community, specifically Argentina, Bolivia, Chile, Colombia, Dominican Republic, Guatemala, Paraguay, and Venezuela

Planetary cartography in the next decade (1984 - 1994)

The cartographic products required to support science and planetary exploration during the next 10 years were assessed. Only major map series or first order maps needed to characterize the surface physiography of a planet or satellite were considered. Included in these considerations are maps needed as bases for plotting geologic, geophysical, and atmospheric phenomena and for planning future planetary exploration. These products consist of three types of maps: controlled photomosaics, shaded relief maps, and topographic contour maps

Automated 3D object modeling from aerial video imagery

Research in physically accurate 3D modeling of a scene is gaining momentum because of its far reaching applications in civilian and defense sectors. The modeled 3D scene must conform both geometrically and spectrally to the real world for all the applications. Geometric modeling of a scene can be achieved in many ways of which the two most popular methods are - a) using multiple 2D passive images of the scene also called as stereo vision and b) using 3D point clouds like Lidar (Light detection and ranging) data. In this research work, we derive the 3D models of objects in a scene using passive aerial video imagery. At present, this geometric modeling requires a lot of manual intervention due to a variety of factors like sensor noise, low contrast conditions during image capture, etc. Hence long time periods, in the order of weeks and months, are required to model even a small scene. This thesis focuses on automating the process of geometric modeling of objects in a scene from passive aerial video imagery. The aerial video frames are stitched into stereo mosaics. These stereo mosaics not only provide the elevation information of a scene but also act as good 3D visualization tools. The 3D information obtained from the stereo mosaics is used to identify the various 3D objects, especially man-made buildings using probabilistic inference provided by Bayesian Networks. The initial 3D building models are further optimized by projecting them on to the individual video frames. The limitations of the state-of-art technology in attaining these goals are presented along with the techniques to overcome them. The improvement that can be achieved in the accuracy of the 3D models when Lidar data is fused with aerial video during the object identification process is also examined

Field reconnaissance geologic mapping of the Columbia Hills, Mars, based on Mars Exploration Rover Spirit and MRO HiRISE observations

Chemical, mineralogic, and lithologic ground truth was acquired for the first time on Mars in terrain units mapped using orbital Mars Reconnaissance Orbiter's High Resolution Imaging Science Experiment (MRO HiRISE) image data. Examination of several dozen outcrops shows that Mars is geologically complex at meter length scales, the record of its geologic history is well exposed, stratigraphic units may be identified and correlated across significant areas on the ground, and outcrops and geologic relationships between materials may be analyzed with techniques commonly employed in terrestrial field geology. Despite their burial during the course of Martian geologic time by widespread epiclastic materials, mobile fines, and fall deposits, the selective exhumation of deep and well-preserved geologic units has exposed undisturbed outcrops, stratigraphic sections, and structural information much as they are preserved and exposed on Earth. A rich geologic record awaits skilled future field investigators on Mars. The correlation of ground observations and orbital images enables construction of a corresponding geologic reconnaissance map. Most of the outcrops visited are interpreted to be pyroclastic, impactite, and epiclastic deposits overlying an unexposed substrate, probably related to a modified Gusev crater central peak. Fluids have altered chemistry and mineralogy of these protoliths in degrees that vary substantially within the same map unit. Examination of the rocks exposed above and below the major unconformity between the plains lavas and the Columbia Hills directly confirms the general conclusion from remote sensing in previous studies over past years that the early history of Mars was a time of more intense deposition and modification of the surface. Although the availability of fluids and the chemical and mineral activity declined from this early period, significant later volcanism and fluid convection enabled additional, if localized, chemical activity

On Martian Surface Exploration: Development of Automated 3D Reconstruction and Super-Resolution Restoration Techniques for Mars Orbital Images

Very high spatial resolution imaging and topographic (3D) data play an important role in modern Mars science research and engineering applications. This work describes a set of image processing and machine learning methods to produce the “best possible” high-resolution and high-quality 3D and imaging products from existing Mars orbital imaging datasets. The research work is described in nine chapters of which seven are based on separate published journal papers. These include a) a hybrid photogrammetric processing chain that combines the advantages of different stereo matching algorithms to compute stereo disparity with optimal completeness, fine-scale details, and minimised matching artefacts; b) image and 3D co-registration methods that correct a target image and/or 3D data to a reference image and/or 3D data to achieve robust cross-instrument multi-resolution 3D and image co-alignment; c) a deep learning network and processing chain to estimate pixel-scale surface topography from single-view imagery that outperforms traditional photogrammetric methods in terms of product quality and processing speed; d) a deep learning-based single-image super-resolution restoration (SRR) method to enhance the quality and effective resolution of Mars orbital imagery; e) a subpixel-scale 3D processing system using a combination of photogrammetric 3D reconstruction, SRR, and photoclinometric 3D refinement; and f) an optimised subpixel-scale 3D processing system using coupled deep learning based single-view SRR and deep learning based 3D estimation to derive the best possible (in terms of visual quality, effective resolution, and accuracy) 3D products out of present epoch Mars orbital images. The resultant 3D imaging products from the above listed new developments are qualitatively and quantitatively evaluated either in comparison with products from the official NASA planetary data system (PDS) and/or ESA planetary science archive (PSA) releases, and/or in comparison with products generated with different open-source systems. Examples of the scientific application of these novel 3D imaging products are discussed

Digital outcrop mapping of a reservoir-scale incised valley fill, Sego Sandstone, Book Cliffs, Utah

Outcrop analog studies have long been used to define subsurface correlation strategies and improve predictions of reservoir heterogeneities that can complicate production behavior. Recent advancements in geographic information software, 3D geologic modeling techniques, and survey equipment have the potential to revolutionize outcrop analog studies. A workflow is developed to create digital outcrop models using a reflectorless total station, a digital camera, Erdas Photogrammetry Module™, and Gocad™ to document complex stratal variations across kilometers-long outcrops. Combining outcrop digital elevation models with orthorectified photographs and detailed sedimentologic logs provides a framework for static 3D reservoir analog models. Developed methodologies are demonstrated by mapping rock variations and stratal geometries within several kilometers-long, sub-parallel exposures of the Lower Sego Sandstone in San Arroyo Canyon, Book Cliffs, Utah. The digital outcrop model of the Lower Sego Sandstone documents complex bedding geometry and facies distribution within two sharp-based sandstone layers. A mapping of allostratigraphic surfaces through the digital outcrop model provided a framework in which to analyze facies variations. These surfaces included: 1) Basal erosion surfaces of these layers interpreted to have formed by tidal erosion of the sea floor during shoreline regression; 2) a high relief erosion surface within the upper layer interpreted to have formed during lowstand fluvial incision; and 3) top contacts of layers defined by abrupt fining to marine shale, which are interpreted to record marine ravinement during transgression. Facies variations within the lower layer include low sinuosity distributary channel deposits incised into highly marine bioturbated sandstone. Deposits above the high-relief erosion surface within the upper layer are a classic valley fill succession, which processes upward from lowstand fluvial channel deposits, to heterolithic estuarine deposits, and finally to sandy landward-dipping beds of an estuarine mouth shoal deposit. The digital outcrop model allows surfaces and facies observation to be mapped within a structured 3D coordinate system to define reservoir analog models

Guidelines for Best Practice and Quality Checking of Ortho Imagery

For almost 10 years JRC's ¿Guidelines for Best Practice and Quality Control of Ortho Imagery¿ has served as a reference document for the production of orthoimagery not only for the purposes of CAP but also for many medium-to-large scale photogrammetric applications. The aim is to provide the European Commission and the remote sensing user community with a general framework of the best approaches for quality checking of orthorectified remotely sensed imagery, and the expected best practice, required to achieve good results. Since the last major revision (2003) the document was regularly updated in order to include state-of-the-art technologies. The major revision of the document was initiated last year in order to consolidate the information that was introduced to the document in the last five years. Following the internal discussion and the outcomes of the meeting with an expert panel it was decided to adopt as possible a process-based structure instead of a more sensor-based used before and also to keep the document as much generic as possible by focusing on the core aspects of the photogrammetric process. Additionally to any structural changes in the document new information was introduced mainly concerned with image resolution and radiometry, digital airborne sensors, data fusion, mosaicking and data compression. The Guidelines of best practice is used as the base for our work on the definition of technical specifications for the orthoimagery. The scope is to establish a core set of measures to ensure sufficient image quality for the purposes of CAP and particularly for the Land Parcel Identification System (PLIS), and also to define the set of metadata necessary for data documentation and overall job tracking.JRC.G.3-Agricultur

Large Area 3-D Reconstructions from Underwater Optical Surveys

Robotic underwater vehicles are regularly performing vast optical surveys of the ocean floor. Scientists value these surveys since optical images offer high levels of detail and are easily interpreted by humans. Unfortunately, the coverage of a single image is limited by absorption and backscatter while what is generally desired is an overall view of the survey area. Recent works on underwater mosaics assume planar scenes and are applicable only to situations without much relief. We present a complete and validated system for processing optical images acquired from an underwater robotic vehicle to form a 3D reconstruction of the ocean floor. Our approach is designed for the most general conditions of wide-baseline imagery (low overlap and presence of significant 3D structure) and scales to hundreds or thousands of images. We only assume a calibrated camera system and a vehicle with uncertain and possibly drifting pose information (e.g., a compass, depth sensor, and a Doppler velocity log). Our approach is based on a combination of techniques from computer vision, photogrammetry, and robotics. We use a local to global approach to structure from motion, aided by the navigation sensors on the vehicle to generate 3D sub-maps. These sub-maps are then placed in a common reference frame that is refined by matching overlapping sub-maps. The final stage of processing is a bundle adjustment that provides the 3D structure, camera poses, and uncertainty estimates in a consistent reference frame. We present results with ground truth for structure as well as results from an oceanographic survey over a coral reef.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86036/1/opizarro-12.pd